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相关概念视频

Deconvolution01:20

Deconvolution

191
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
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Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

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The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
6.4K
Phase Contrast and Differential Interference Contrast Microscopy01:26

Phase Contrast and Differential Interference Contrast Microscopy

8.2K
Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
8.2K
Positron Emission Tomography01:29

Positron Emission Tomography

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Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body...
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Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

4.8K
Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
4.8K
Computed Tomography01:10

Computed Tomography

4.6K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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相关实验视频

Updated: Jul 22, 2025

Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects
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Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects

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高质量和高多样性的条件生成幽灵成像,基于无声扩散概率模型.

Shuai Mao, Yuchen He, Hui Chen

    Optics express
    |July 21, 2023
    PubMed
    概括

    我们介绍了DDPMGI,这是一种用于幽灵成像 (GI) 的新型深度学习方法,可以提高图像重建质量和多样性. 这种方法甚至在有限的数据的情况下也显著改善了结果,超过了现有的技术.

    科学领域:

    • 计算机成像成像技术
    • 机器学习用于光学系统.

    背景情况:

    • 深度学习 (DL) 方法对幽灵成像 (GI) 重建有希望.
    • 目前的DL-GI方法通常专注于像素级准确性,忽视重建多样性.
    • 现有的方法可能无法充分利用改善GI的条件概率.

    研究的目的:

    • 开发基于DL的GI方法,以提高重建质量和多样性.
    • 通过结合概率模型来解决当前DL-GI技术的局限性.
    • 通过模拟和物理实验验证拟议的方法.

    主要方法:

    • 用于GI. 用于GI. 用于GI. 用于GI. 用于GI. 用于GI. 用于GI. 用于GI.
    • 开发了一种名为DDPMGI的新方法用于图像重建.
    • 在低取样率 (10%) 和彩色GI重建中评估性能.

    主要成果:

    • 与其他方法相比,DDPMGI实现了优越的图像质量和重建多样性.
    • 在10%的采样率下,DDPMGI的平均PSNR为21.19dB,SSIM为0.64.
    • 在彩色GI重建中成功应用,平均PSNR为20.055dB,SSIM为0.723.

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    结论:

    • DDPMGI在高质量的胃肠道图像重建方面取得了重大进展.
    • 该方法在现实场景和彩色成像中表现出有效性.
    • DDPMGI为多样化和准确的GI重建提供了一个强大的框架.